Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life
Human motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential technolog...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-11-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/11/28435 |
| _version_ | 1798026861267124224 |
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| author | Alessandro Tognetti Federico Lorussi Nicola Carbonaro Danilo de Rossi |
| author_facet | Alessandro Tognetti Federico Lorussi Nicola Carbonaro Danilo de Rossi |
| author_sort | Alessandro Tognetti |
| collection | DOAJ |
| description | Human motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential technologies for daily life situations. We developed and conducted a preliminary evaluation of an innovative sensing concept that combines e-textiles and tri-axial accelerometers for ambulatory human motion analysis. Our sensory fusion method is based on a Kalman filter technique and combines the outputs of textile electrogoniometers and accelerometers without making any assumptions regarding the initial accelerometer position and orientation. We used our technique to measure the flexion-extension angle of the knee in different motion tasks (monopodalic flexions and walking at different velocities). The estimation technique was benchmarked against a commercial measurement system based on inertial measurement units and performed reliably for all of the various tasks (mean and standard deviation of the root mean square error of 1:96 and 0:96, respectively). In addition, the method showed a notable improvement in angular estimation compared to the estimation derived by the textile goniometer and accelerometer considered separately. In future work, we will extend this method to more complex and multi-degree of freedom joints. |
| first_indexed | 2024-04-11T18:43:12Z |
| format | Article |
| id | doaj.art-aa3f578f6edb4c03b742f2c905dfb235 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:43:12Z |
| publishDate | 2015-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-aa3f578f6edb4c03b742f2c905dfb2352022-12-22T04:08:56ZengMDPI AGSensors1424-82202015-11-011511284352845510.3390/s151128435s151128435Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily LifeAlessandro Tognetti0Federico Lorussi1Nicola Carbonaro2Danilo de Rossi3Research Center E.Piaggio, University of Pisa, Largo L. Lazzarino 1, 56126 Pisa, ItalyResearch Center E.Piaggio, University of Pisa, Largo L. Lazzarino 1, 56126 Pisa, ItalyResearch Center E.Piaggio, University of Pisa, Largo L. Lazzarino 1, 56126 Pisa, ItalyResearch Center E.Piaggio, University of Pisa, Largo L. Lazzarino 1, 56126 Pisa, ItalyHuman motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential technologies for daily life situations. We developed and conducted a preliminary evaluation of an innovative sensing concept that combines e-textiles and tri-axial accelerometers for ambulatory human motion analysis. Our sensory fusion method is based on a Kalman filter technique and combines the outputs of textile electrogoniometers and accelerometers without making any assumptions regarding the initial accelerometer position and orientation. We used our technique to measure the flexion-extension angle of the knee in different motion tasks (monopodalic flexions and walking at different velocities). The estimation technique was benchmarked against a commercial measurement system based on inertial measurement units and performed reliably for all of the various tasks (mean and standard deviation of the root mean square error of 1:96 and 0:96, respectively). In addition, the method showed a notable improvement in angular estimation compared to the estimation derived by the textile goniometer and accelerometer considered separately. In future work, we will extend this method to more complex and multi-degree of freedom joints.http://www.mdpi.com/1424-8220/15/11/28435wearable goniometersaccelerometersdata fusionhuman motion analysisjoint angle measurementsknitted piezoresistive fabricssmart textilessensor to segment alignmentknee joint |
| spellingShingle | Alessandro Tognetti Federico Lorussi Nicola Carbonaro Danilo de Rossi Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life Sensors wearable goniometers accelerometers data fusion human motion analysis joint angle measurements knitted piezoresistive fabrics smart textiles sensor to segment alignment knee joint |
| title | Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life |
| title_full | Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life |
| title_fullStr | Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life |
| title_full_unstemmed | Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life |
| title_short | Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life |
| title_sort | wearable goniometer and accelerometer sensory fusion for knee joint angle measurement in daily life |
| topic | wearable goniometers accelerometers data fusion human motion analysis joint angle measurements knitted piezoresistive fabrics smart textiles sensor to segment alignment knee joint |
| url | http://www.mdpi.com/1424-8220/15/11/28435 |
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